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At least 163 records · Page 9

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Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗

NASA NTRS1981

The retarding ion mass spectrometer on dynamics Explorer-A

An instrument designed to measure the details of the thermal plasma distribution combines the ion temperature-determining capability of the retarding potential analyzer with the compositional capabilities of the mass spectrometer and adds multiple sensor heads to sample all directions relative to the spacecraft ram directions. The retarding ion mass spectrometer, its operational modes and calibration are described as well as the data reduction plan, and the anticipated results.

Chappell, C. R.↗

NASA NTRS1981

Remote sensing of temperature profiles in vegetation canopies using multiple view angles and inversion techniques

A mathematical method is presented which allows the determination of vertical temperature profiles of vegetation canopies from multiple sensor view angles and some knowledge of the vegetation geometric structure. The technique was evaluated with data from several wheat canopies at different stages of development, and shown to be most useful in the separation of vegetation and substrate temperatures with greater accuracy in the case of intermediate and dense vegetation canopies than in sparse ones. The converse is true for substrate temperatures. Root-mean-square prediction accuracies of temperatures for intermediate-density wheat canopies were 1.8 C and 1.4 C for an exact and an overdeterminate system, respectively. The findings have implication for remote sensing research in agriculture, geology or other earth resources disciplines.

Kimes, D. S.↗

NASA NTRS1982

Instrument manual for the retarding ion mass spectrometer on Dynamics Explorer-1

The retarding ion mass spectrometer (RIMS) for Dynamics Explorer-1 is an instrument designed to measure the details of the thermal plasma distribution. It combines the ion temperature determining capability of the retarding potential analyzer with the compositional capabilities of the mass spectrometer and adds multiple sensor heads to sample all directions relative to the spacecraft ram direction. This manual provides a functional description of the RIMS, the instrument calibration, and a description of the commands which can be stored in the instrument logic to control its operation.

Fields, S. A.↗

NASA NTRS1983

Introduction to acoustic emission

Typical acoustic emission signal characteristics are described and techniques which localize the signal source by processing the acoustic delay data from multiple sensors are discussed. The instrumentation, which includes sensors, amplifiers, pulse counters, a minicomputer and output devices is examined. Applications are reviewed.

Possa, G.↗

NASA NTRS1985

A retarding ion mass spectrometer for the Dynamics Explorer-1

The Retarding Ion Mass Spectrometer (RIMS) for Dynamics Explorer-1 is an instrument designed to measure the details of the thermal plasma distribution. It combines the ion temperature determining capability of the retarding potential analyzer with the compositional capabilities of the mass spectrometer and adds multiple sensor heads to sample all directions relative to the spacecraft ram direction. This manual provides a functional description of the RIMS, the instrument calibration, and a description of the commands which can be stored in the instrument logic to control its operation.

Wright, W.↗

NASA NTRS1985

Integrated multi-sensory control of space robot hand

Dexterous manipulation of a robot hand requires the use of multiple sensors integrated into the mechanical hand under distributed microcomputer control. Where space applications such as construction, assembly, servicing and repair tasks are desired of smart robot arms and robot hands, several critical drives influence the design, engineering and integration of such an electromechanical hand. This paper describes a smart robot hand developed at the Jet Propulsion Laboratory for experimental use and evaluation with the Protoflight Manipulator Arm (PFMA) at the Marshall Space Flight Center (MSFC).

Bejczy, A. K.↗

NASA NTRS1988

Real-time control for manufacturing space shuttle main engines: Work in progress

During the manufacture of space-based assemblies such as Space Shuttle Main Engines, flexibility is required due to the high-cost and low-volume nature of the end products. Various systems have been developed pursuing the goal of adaptive, flexible manufacturing for several space applications, including an Advanced Robotic Welding System for the manufacture of complex components of the Space Shuttle Main Engines. The Advanced Robotic Welding System (AROWS) is an on-going joint effort, funded by NASA, between NASA/Marshall Space Flight Center, and two divisions of Rockwell International: Rocketdyne and the Science Center. AROWS includes two levels of flexible control of both motion and process parameters: Off-line programming using both geometric and weld-process data bases, and real-time control incorporating multiple sensors during weld execution. Both control systems were implemented using conventional hardware and software architectures. The feasibility of enhancing the real-time control system using the problem-solving architecture of Schemer is investigated and described.

Ruokangas, Corinne C.↗

NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗

NASA NTRS1989

Autonomous exploration system: Techniques for interpretation of multispectral data

An on-board autonomous exploration system that fuses data from multiple sensors, and makes decisions based on scientific goals is being developed using a series of artificial neural networks. Emphasis is placed on classifying minerals into broad geological categories by analyzing multispectral data from an imaging spectrometer. Artificial neural network architectures are being investigated for pattern matching and feature detection, information extraction, and decision making. As a first step, a stereogrammetry net extracts distance data from two gray scale stereo images. For each distance plane, the output is the probable mineral composition of the region, and a list of spectral features such as peaks, valleys, or plateaus, showing the characteristics of energy absorption and reflection. The classifier net is constructed using a grandmother cell architecture: an input layer of spectral data, an intermediate processor, and an output value. The feature detector is a three-layer feed-forward network that was developed to map input spectra to four geological classes, and will later be expanded to encompass more classes. Results from the classifier and feature detector nets will help to determine the relative importance of the region being examined with regard to current scientific goals of the system. This information is fed into a decision making neural net along with data from other sensors to decide on a plan of activity. A plan may be to examine the region at higher resolution, move closer, employ other sensors, or record an image and transmit it back to Earth.

Yates, Gigi↗

NASA NTRS1989

A perception system for a planetary explorer

To perform planetary exploration without human supervision, a complete autonomous robot must be able to model its environment and to locate itself while exploring its surroundings. For that purpose, the authors propose a modular perception system for an autonomous explorer. The perception system maintains a consistent internal representation of the observed terrain from multiple sensor views. The representation can be accessed from other modules through queries. The perception system is intended to be used by the Ambler, a six-legged vehicle being built at CMU. A partial implementation of the system using a range scanner is presented as well as experimental results on a testbed that includes the sensor, one computer-controlled leg, and obstacles on a sandy surface.

Hebert, M.↗

NASA NTRS1991

Quantitative knowledge acquisition for expert systems

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

Belkin, Brenda L.↗

NASA NTRS1991

Knowledge acquisition for expert systems using statistical methods

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. A statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors is presented. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development of a Navigation Sensor Management (NSM) Expert System from Kalman Filter covariance data is described. The development method invokes two statistical techniques: Analysis-of-Variance (ANOVA) and the ID3 algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithm identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set.

Belkin, Brenda L.↗

NASA NTRS1991

The spatial characteristics of the B helical mode for a choked axisymmetric nozzle

An acoustic near-field study was performed for an axisymmetric conical nozzle operated at a fully expanded Mach number of 1.3. The acoustic measurements were performed in the nozzle exit plane using multiple sensors arranged around the periphery of the nozzle. The acquired data were simultaneously digitized. The acoustic spatial characteristics, describing the large scale structure associated with the preferred shear layer instability mode, were determined for the dominant B screech mode. The nozzle was fitted with a lip thickening device to determine the effect of this geometric variable on the spatial structure of the jet. For the thin-lipped configuration, the flapping structure of the B screech mode was found to precess in a time-dependent manner about the jet axis. An increasing of the nozzle exit lip thickness altered the spatial characteristics of this mode from a flapping to a time-dependent flapping or spinning. Using the auto-bicoherence spectrum, frequency dependencies were found to exist in the acoustic data of the thick-lipped configuration. These dependencies may be related to the nonlinearity of the jet and/or the time-dependent nature of the B mode spatial structure.

Ponton, Michael K.↗

NASA NTRS1991

Automated site characterization for robotic sample acquisition systems

A mobile, semi-autonomous vehicle with multiple sensors and on-board intelligence is proposed for performing preliminary scientific investigations on extraterrestrial bodies prior to human exploration. Two technologies, a hybrid optical-digital computer system based on optical correlator technology and an image and instrument data analysis system, provide complementary capabilities which might be part of an instrument package for an intelligent robotic vehicle. The hybrid digital-optical vision system could perform real-time image classification tasks using an optical correlator with programmable matched filters under control of a digital microcomputer. The data analysis system would analyze visible and multiband imagery to extract mineral composition and textural information for geologic characterization. Together these technologies would support the site characterization needs of a robotic vehicle for both navigational and scientific purposes.

Scholl, Marija S.↗

NASA NTRS1992

Dual-arm supervisory and shared control space servicing task experiments

A dual-arm task execution primitive has been implemented for cooperative dual-arm telerobotic task execution utilizing multiple sensors concurrently. The primitive has been integrated into a telerobot task execution system and can be called by a task planning system for execution of tasks requiring dual-arm sensor based motion, e.g., force control, teleoperation, and shared control. The primitive has a large input parameter set which is used to specify the desired behavior of the motion. Move-squeeze decomposition is utilized to decompose forces sensed at the wrists of the two manipulators into forces in the move subspace, which cause system motion, and forces in the squeeze subspaces, which cause internal forces. The move and squeeze forces are then separately controlled. Several space servicing tasks utilizing the cooperative dual-arm control capability are described, and experimental results from the tasks are given. The supervisory and shared control tasks include capture of a rotating satellite, orbital replacement unit changeout, fluid coupler seating and locking, and contour following.

Backes, Paul G.↗

NASA NTRS1992

Contact detection and contact motion for error recovery in the presence of uncertainties

Due to various kinds of uncertainties, a robot motion may fail and result in some unintended contact between the object held by the robot and the environment, which greatly hampers robotics applications on tasks with high-precision requirements, such as assembly tasks. Aiming at automatically recovering a robotic task from such a failure, this paper discusses, in the presence of uncertainties, contact detection based on contact motion for recovery. It presents a framework for on-line recognizing contacts using multiple sensor modalities in the presence of sensing uncertainties and means for ensuring successful compliant motions in the presence of sensing and control uncertainties.

Xiao, Jing↗

NASA NTRS1992

The fusion of information via fuzzy integration

Multisensor fusion is becoming increasingly important in intelligent computer vision systems. In this paper we present the generalized fuzzy integral with respect to an S-decomposable measure as a tool for fusing information from multiple sensors in an object recognition problem. Results from an experiment with automatic target recognition imagery are provided.

Keller, James M.↗